Calculating average in panda depending on a name of a other column

Question

I have two columns like this.

   name     length
0   Pk      78
2   Pk      59
4   Pk      283
6   Ser     100
7   Ig_2    79
8   Ig_2    77
9   Ser     369

I want to calculate the average of each name. For example

Pk - 140
ser -234.5
Ig_2 -78

How can i do this with python panda.

I was trying this.

df.groupby(level=0).mean()

but didn't work. Is there anyway to use rolling() function for this?

@AlexanderCécile Sorry, it was a mistake. I have formatted the data — bob, Dec 16 '19 at 22:08
Also what does _didn’t work_ mean, exactly? Did you look at the docs to see what the `level` parameter does? — AMC, Dec 16 '19 at 22:35

Osman Mamun · Accepted Answer · 2019-12-16T22:32:00.773

1

In [1]: import pandas as pd
In [2]: df = pd.DataFrame([['pk', 78], ['pk', 59], ['Ig', 79], ['Ig', 77]], colu
   ...: mns=['name', 'length'])

In [3]: df
Out[3]:
  name  length
0   pk      78
1   pk      59
2   Ig      79
3   Ig      77

In [4]: df.groupby('name').mean()
Out[4]:
      length
name
Ig      78.0
pk      68.5

To sort values in ascending order:

In [11]: df.groupby('name').mean().sort_values(by='length', 
ascending=True)
Out[11]:
      length
name
pk      68.5
Ig      78.0

edited Dec 16 '19 at 22:32

answered Dec 16 '19 at 22:12

Osman Mamun

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Thank you very much. Can you tell me how can i make it in ascending order. i mean the answer – bob Dec 16 '19 at 22:26
1

`df.groupby('name').mean().sort_values(by='length', ascending=True)` – Osman Mamun Dec 16 '19 at 22:32

Calculating average in panda depending on a name of a other column

1 Answers1